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MSys

Senior Azure Data Engineer -Hybrid

Pay: Not specified

Posted: 5 days ago

Location: Raleigh, NC (Hybrid)

Last Updated: 3 days ago

Hours: Full-Time

Expires: 9/30/2026

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What they do

A Data Engineer designs, builds and manages the information or big data infrastructure. Develops the architecture that helps analyze and process data in the way the organization needs it. Makes sure those systems are performing smoothly.

$113,693 / year median in North Carolina

+14% projected growth

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Job Description

Interview Type:

Webcam Interview Only

Very long term project; initial PO for 1 year, expect to go for 4+ years
Hybrid
Description The Client requires the assistance of a contract resource to serve as a Data Engineer responsible for the design, development, and optimization of data pipelines and analytics solutions/dashboards on cloud-based data platforms.

This work will leverage Azure Synapse Analytics, Power BI, and integrations with Salesforce or Curam/Oracle to support program needs. Key Responsibilities Analyze source systems and design, develop, and maintain scalable ETL/ELT pipelines using Azure Synapse, Azure Data Factory, and related Azure services. Build and manage data ingestion workflows from Salesforce, including API integrations, schema alignment, and performance tuning. Develop and maintain data models, data transformations, and semantic layers to support Power BI reporting and analytics. Optimize Synapse pipelines, SQL queries, and data storage for performance, reliability, and cost efficiency. Troubleshoot pipeline failures, Salesforce API issues, and Power BI dataset/dataflow refresh problems.

Skills/Requirements:

Skill Required Years Strong Hands-on experience configuring, designing, developing and testing dashboards using Power BI Required 5 Years Experience supporting Power BI datasets, dataflows, and DirectQuery/Import models. Required 5 Years Experience working with structured and semi-structured data formats (JSON, CSV, Parquet, etc.). Required 3 Years Strong experience in designing and optimizing scalable data pipelines using modern platforms like Azure Synapse, Snowflake or Databricks workflows Required 3

Years SQL Mastery:

Advanced query writing, ETL/ELT, performance tuning, and optimization. Required 5

Years Programming Languages:

Strong proficiency in Python or Scala for data processing. Required 3 Years Hands-on experience in developing efficient PL/SQL procedures Required 5 Years Experience with Programming and Scripting (SQL, T-SQL, and data query optimization) Required 2 Years Solid understanding of Azure cloud services (Synapse, Data Lake, Data Factory, Azure SQL, monitoring tools). Required 2 Years Experience in Azure Data Lake Storage (ADLS), Delta Lake, and data modeling concepts and Warehousing (star schema, snowflake schema) Required 2 Years